另外即使谈到物理上的tensor，近年也有结合深度学习和Tensor Network的工作，实际上使用张量网络来降低NN里...
In [7]: t.storage() Out[7]: 2.0 3.0 4.0 5.0 6.0 7.0 [torch.FloatStorage of size 6] 需要注意的是tensor可以只是part of a storage,比如接下来的例子中t_ 只有3个元素,但它的storage仍然是6个元素 In [4]: t_= t[1] In [5]: t_ Out[5]: tensor([5., 6., 7.]) In [6]: t_....
Ansor:Generating High-Performance Tensor Program for Deep Learning Abstract 高性能的张量程序对于保证深度神经网络的高效执行十分关键,但是在不同硬件平台上获取高性能的张量程序并不容易。近年的研究中,深度学习系统依赖硬件供应商提供的算子库,或者多种搜索策略来获得高性能的张量程序。这些方法可能需要较多的工程上的...
The slow compilation process is due to the large search space formulated by existing DNN compilers, which have to use machine learning algorithms to find good solutions. In this paper, we present ROLLER, which takes a different construction-based approach to generate kernels. At the ...
Tensor2Tensor was used to develop a number of state-of-the-art models and deep learning methods. Here we list some papers that were based on T2T from the start and benefited from its features and architecture in ways described in theGoogle Research Blog post introducing T2T. ...
Package tensor is a package that provides efficient, generic (by some definitions of generic) n-dimensional arrays in Go. Also in this package are functions and methods that are used commonly in arithmetic, comparison and linear algebra operations....
methods. Furthermore, it can be generalized from piecewise linear to higher-order polynomials. Also, more sophisticated basis functions like interpolets, prewavelets, or wavelets can be used in a straightforward way.We describe the basic features of sparse grids and report the results of various...
The increasing demand for improving deep learning model performance has led to a paradigm shift in supporting low-precision computation to harness the robustness of deep learning to errors. Despite the emergence of new low-precision data types and o...
His research is mainly focused on artificial intelligence, computer vision, high-performance computing, cloud computing, distributed computing, parallel computing, eHealth, simulations, and statistical methods. He hasReferences (100) J. Schmidhuber Deep learning in neural networks: an overview Neural Netw...
Machine Learning Feature engineering, structuring unstructured data, and lead scoring Shaw Talebi August 21, 2024 7 min read Solving a Constrained Project Scheduling Problem with Quantum Annealing Data Science Solving the resource constrained project scheduling problem (RCPSP) with D-Wave’s hybrid constr...